Papers

4

Total Citations

25

H-Index

3

About

M. Sabarimalai Manikandan is a leading researcher in audio signal processing and intelligent sensing systems, with a focus on developing context-aware computing technologies. His major contributions span automatic audio event recognition (AER) and sound source localization, where he has designed frameworks that enable machines to interpret and respond to their auditory environment—critical for applications in audio surveillance, robotics, and machine health monitoring. His 2019 paper on AER schemes, which has garnered 14 citations, lays foundational work for building intelligent, location-aware devices. Manikandan has also advanced human-computer interaction through deep learning-based hand gesture recognition using high-resolution thermal imaging, addressing performance limitations of conventional vision-based methods. More recently, his work on deep learning for soldier face detection and counting demonstrates the application of AI in tactical operations and autonomous navigation. With a growing citation impact and a portfolio that bridges audio computing, computer vision, and defense technologies, Manikandan’s research is shaping the next generation of autonomous and context-aware systems.

Research Focus

Key Achievements

3
H-Index
4
Papers
25
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Automatic Audio Event Recognition Schemes for Context-Aware Audio Computing Devices
14 citations · 2019
📈 Most Prolific Year: 2019 (2 Papers)
🤝 Key Collaborators: 12
🏛 Institutions: Indian Institute of Technology Bhubaneswar, University of Agder, Indian Institute of Technology Palakkad

Top Papers

  1. 1
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  4. 4

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago